Indian Institute of Technology (IIT) researchers created a flavor network in which food ingredients are linked if they appear together in the same recipe.
The researchers used the online cooking database TarlaDalal.com to download more than 2,500 recipes, containing 194 ingredients, to create the network. The researchers wanted to discover, using big data phenomena such as clustering effects, if ingredients sharing flavor compounds occur in the same recipe more often than if the ingredients were chosen at random.
The researchers found Indian cuisine is characterized by strong negative food pairing; they also found specific ingredients dramatically effect food pairing. For example, the presence of ingredients such as cayenne pepper, green bell pepper, coriander, garam masala, tamarind, ginger, and cinnamon strongly biases the flavor-sharing pattern of Indian cuisine toward negative pairing.
"Our study reveals that spices occupy a unique position in the ingredient composition of Indian cuisine and play a major role in defining its characteristic profile," IIT researcher Anupam Jain said.
"Our study could potentially lead to methods for creating novel Indian signature recipes, healthy recipe alterations, and recipe recommender systems," the researchers say.
From Technology Review
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